Feature Request Description:

This request comes from travel and agency-based businesses that handle a high volume of daily inquiries, often from the same customer multiple times within a single day. To maintain service quality and optimize operations, they require more detailed visibility into agent performance and conversation handling.

Currently, the exported Conversation Analytics data does not provide sufficient granularity for accurate performance tracking. Critical information such as session-based data (from open to closed conversations), agent/participant names, precise timestamps, and customer identifiers is either missing or not structured for effective analysis.

As a result, businesses are unable to reliably measure key metrics, including:

First response time

Resolution time

SLA compliance per interaction

Agent-level activity and performance

We propose enhancing the Conversation Analytics export to include:

Session-based records (each conversation lifecycle from open to closed)

Agent/participant attribution for every interaction

Detailed timestamps for key events (e.g., first response, last reply, closure)

Customer identifiers such as phone number or room/chat ID to distinguish repeated inquiries from the same user

Structured, analysis-ready data format for reporting

With these improvements, customers will be able to accurately track individual interactions—even multiple inquiries from the same customer within a day—and efficiently evaluate agent performance. This will enable more reliable daily reporting, better SLA monitoring, and overall improvement in service quality using a single exported file.